code: def test_ablation_flip_changes_pred_class(self):
      ex = {"sentence": "this long movie is terrible"}
      ex_output = list(self.classification_model.predict([ex]))[0]
      pred_class = str(np.argmax(ex_output["probas"]))
      self.assertEqual("0", pred_class)
      self.classification_config[ablation_flip.FIELDS_TO_ABLATE_KEY] = [
          "sentence"
      ]
      cfs = self.ablation_flip.generate(
          ex,
          self.classification_model,
          None,
          self.classification_config,
      )
      cf_outputs = self.classification_model.predict(cfs)
      for cf_output in cf_outputs:
          self.assertNotEqual(
              np.argmax(ex_output["probas"]),
              np.argmax(cf_output["probas"]),
          )
  
imports: from collections.abc import Iterable, Iterator
  from absl.testing import absltest
  from lit_nlp.api import types
  from lit_nlp.components import ablation_flip
  from lit_nlp.examples.models import glue_models
  import numpy
  from lit_nlp.lib import file_cache
label_desc: Use image node_id 10 for calling the ModelBasedAblationFlipTest obj's underlying member method code with example usage: obj.test_ablation_flip_changes_pred_class() without return types